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Forecasting Models of Retail Rents

Author

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  • Chris Brooks

    (ISMA Centre, Department of Economics, University of Reading, Whiteknights, Reading RG6 6BA, England)

  • Sotiris Tsolacos

    (Jones Lang LaSalle, 22 Hanover Square, London W1A 2BN, England)

Abstract

The authors model retail rents in the United Kingdom with use of vector-autoregressive and time-series models. Two retail rent series are used, compiled by LaSalle Investment Management and CB Hillier Parker, and the emphasis is on forecasting. The results suggest that the use of the vector-autoregression and time-series models in this paper can pick up important features of the data that are useful for forecasting purposes. The relative forecasting performance of the models appears to be subject to the length of the forecast time-horizon. The results also show that the variables which were appropriate for inclusion in the vector-autoregression systems differ between the two rent series, suggesting that the structure of optimal models for predicting retail rents could be specific to the rent index used. Ex ante forecasts from our time-series suggest that both LaSalle Investment Management and CB Hillier Parker real retail rents will exhibit an annual growth rate above their long-term mean.

Suggested Citation

  • Chris Brooks & Sotiris Tsolacos, 2000. "Forecasting Models of Retail Rents," Environment and Planning A, , vol. 32(10), pages 1825-1839, October.
    • Handle: RePEc:sae:envira:v:32:y:2000:i:10:p:1825-1839
    DOI: 10.1068/a3332
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    References listed on IDEAS

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    Cited by:

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    2. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    3. Catherine Jackson, 2006. "Retail planning and institutional property investment," Regional Studies, Taylor & Francis Journals, vol. 40(5), pages 555-561.
    4. Catherine Jackson, 2002. "Classifying Local Retail Property Markets on the Basis of Rental Growth Rates," Urban Studies, Urban Studies Journal Limited, vol. 39(8), pages 1417-1438, July.
    5. Dimitrios Papastamos & George Matysiak & Simon Stevenson, 2014. "A Comparative Analysis of the Accuracy and Uncertainty in Real Estate and Macroeconomic Forecasts," Real Estate & Planning Working Papers rep-wp2014-06, Henley Business School, University of Reading.
    6. Kim Hin David Ho & Satyanarain Rengarajan, 2017. "Industrial Real Estate Market Dynamics in Singapore: A VAR Approach," International Real Estate Review, Global Social Science Institute, vol. 20(4), pages 417-450.
    7. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2012. "Examination of property forecasting models - accuracy and its improvement through combination forecasting," ERES eres2012_082, European Real Estate Society (ERES).

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